Ontology extraction from tables on the Web

Tanaka, M.; Ishida, Toru

doi:10.1109/saint.2006.45

Cited by 10 publications

(7 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The current version of Project Organizer demands a lot of manual work by the project manager and some dorm of automation such as automatic metadata extraction from semi-structured tables [8] is needed to ease this burden.…”

Section: Resultsmentioning

confidence: 99%

Content management for inter-organizational projects using e-mail metaphor

Nakatsuka

Ishida

2006

International Symposium on Applications and the Internet (SAINT'06)

Self Cite

View full text Add to dashboard Cite

show abstract

Section: Resultsmentioning

confidence: 99%

Content management for inter-organizational projects using e-mail metaphor

Nakatsuka

Ishida

2006

International Symposium on Applications and the Internet (SAINT'06)

Self Cite

View full text Add to dashboard Cite

show abstract

“…Several researchers have reported their work on extracting information from the web table [1][2][3][4][5][6][7][8]. In [1][2], Jung et al used a machine learning algorithm C4.5 to separate the table head from the body according to rows and columns' characteristics [1], and complemented the head extraction method with supplementary heuristic rules [2].…”

Section: Related Workmentioning

confidence: 99%

Analysis and Interpretation of Semantic HTML Tables

Yin

Guo

et al. 2009

Web Information Systems and Mining

View full text Add to dashboard Cite

Table is an effective manifestation of structural knowledge, on which the semantic analysis is a very important part in semantic document analysis. To interpret the structure and the semantic relations of the HTML documents, definitions of normalized table and tabular coordinate system are proposed according to database relation theory. This paper classifies cells into normalized cells and visual cells, indicates that row or column and its combined cell are the primary semantic expression forms of table and nested tables are the further expansion of a certain table cell. Finally, a table analyzing algorithm is given based on tabular coordinate system. Practice shows that the algorithm is simple, fast and having certain practical significance.

show abstract

“…Tijerino et al [22] described the automatic generation of ontologies from the normalized tables, which is a structure they got after normalizing table-equivalent data. Tanaka et al [23] proposed a method for extracting relations based on interpretations given by humans, in order to interpret structures of each tables correctly. This method is easy to apply to tables in various domains because it uses interpretations given by humans and generalized table structures instead of a domain-specific knowledge base.…”

Section: Introductionmentioning

confidence: 99%

A Bootstrapping Method for Automatic Constructing of the Web Ontology Instances and Properties

Cha¹,

Han²

2018

IJWesT

View full text Add to dashboard Cite

With the phenomenal growth of the Web resources, to construct ontologies by using existing resources structured in the Web has gotten more and more attention. Previous studies for constructing ontologies from the Web have not carefully considered all the semantic features of the Web documents. Hereby it is difficult to correctly construct ontology elements from the Web documents that are increasing daily. The machine learning methods play an important role in automatic constructing of the Web ontology. Bootstrapping technique is a semi-supervised learning method that can automatically generate many terms from the few seed terms entered by human. This paper proposes bootstrapping method that can automatically construct instances and data type properties of the Web ontology, taking proper noun as semantic core element of the Web table. Experimental result shows that proposed method can rapidly and effectually construct instances and its properties of the Web ontology.

show abstract

Ontology extraction from tables on the Web

Abstract: Abstract

Cited by 10 publications

References 14 publications

Content management for inter-organizational projects using e-mail metaphor

Content management for inter-organizational projects using e-mail metaphor

Analysis and Interpretation of Semantic HTML Tables

A Bootstrapping Method for Automatic Constructing of the Web Ontology Instances and Properties

Contact Info

Product

Resources

About